Reliable local data for effective prevention of intimate partner violence in India
Authors: Seema Sahay, Sampada Bangar, Ameeta S Kalokhe
Journal: The Lancet Global Health (2023)

The UN Sustainable Development Goals call for the elimination of violence against women and girls and for the capture and assessment of disaggregated data to ensure that “no one is left behind”.1Food and Agriculture Organization of the UNGuidelines on data disaggregation for SDG Indicators using survey data.https://www.fao.org/documents/card/en/c/cb3253enDate: 2021Date accessed: August 22, 2023Google Scholar, 2UNTransforming our world: the 2030 Agenda for Sustainable Development.https://sdgs.un.org/2030agendaDate: 2015Date accessed: August 28, 2023Google Scholar In India, according to the 2019–21 National Family Health Survey (NFHS-5),3Ministry of Health and Family WelfareGovernment of IndiaInternational Institute for Population SciencesIndia and ICF–National Family Health Survey (NFHS5), 2019–21. International Institute for Population Sciences, Mumbai, India2021Google Scholar 29% of women who had ever been married reported physical or sexual intimate partner violence (IPV); thus, improved IPV prevention in India is crucial. India has substantial heterogeneity within and across states by history, culture, resources, and social structures, each of which influence the risk of IPV. However, the NFHS only provides IPV estimates at national and state levels. Because of the heterogeneity of the Indian population, local disaggregated estimates of IPV are crucial to guide the prioritisation of IPV prevention and support services, to develop contextually adapted IPV-prevention interventions, and to ultimately enable accurate evaluation of local IPV-prevention programmes. In this issue of The Lancet Global Health, Srivastava and colleagues4Srivastava S Kumar K McDougal L et al.Spatial heterogeneity in intimate partner violence across the 640 districts of India: a secondary analysis of a cross-sectional, population-based survey by use of model-based small-area estimation.Lancet Glob Health. 2023; 11: e1587-e1597Google Scholar use model-based small-area estimation techniques linking data from the 2015–16 NFHS-4 and the 2011 Indian Population and Housing Census (2011 Indian Census) to provide reliable, district-level IPV estimates for the previous 12 months. Their findings show considerable intrastate and interstate IPV variation in the reporting of physical, sexual, and emotional IPV. For example, in the northern state of Bihar, which had the highest state-level physical IPV prevalence (35·1%, 95% CI 33·3–37·0), district-level estimates ranged from 23·5% (23·0–23·9) in Siwan to 42·7% (42·3–43·1%) in Purbi Champaran. Using spatial-heterogeneity analysis, the authors also identify several IPV hotspots (ie, clusters of districts that have a high prevalence of IPV in India), IPV coldspots (ie, clusters of districts that have a low prevalence of IPV in India), and heterogeneity in spatial clusters by IPV type—with hotspots for physical, sexual, and emotional IPV not necessarily spatially overlapping. The Article has crucial policy, prevention-programme, and research implications. In India, a resource-limited, populous country, district-level IPV estimates can more effectively guide programmes and policy makers to provide contextually appropriate resources than state-level estimates. We commend the authors for showcasing the effectiveness of small-area estimation techniques in identifying hotspots with larger burdens of IPV than other regions. This identification potentially enables the sharing of effective methods and practices from low-IPV districts (eg, East Sikkim district of Sikkim [1·1%, 95% CI 0·7–1·4], Hamirpur district of Himachal Pradesh [2·0%, 0·5–3·5], and North Goa [0·1%, 0·1–0·2]) with high-IPV districts or clusters. Future qualitative exploration of and assessments of policy and programme strengths in low-IPV districts are needed to inform policies and programmes in other regions; exploration of IPV determinants and needs assessments of high-IPV districts are needed to inform IPV interventions. Furthermore, these district-level estimates enable the evaluation of the effects of local IPV programmes and policies that could have remained undetected if IPV trends were only examined at the state level. Although the Article by Srivastava and colleagues has crucial implications for IPV prevention in India, their findings should be interpreted and disseminated with caution. First, the limitations of the datasets that were used to calculate IPV estimates should be recognised. The 2011 Indian Census data are now 12 years old; thus, many auxiliary variables (eg, sex ratio at birth, amount of female workforce participation and sex gap relative to male workforce participation, and urban residence) that were used in the analysis have changed.3Ministry of Health and Family WelfareGovernment of IndiaInternational Institute for Population SciencesIndia and ICF–National Family Health Survey (NFHS5), 2019–21. International Institute for Population Sciences, Mumbai, India2021Google Scholar, 5Office of the Registrar General and Census CommissionerCensus tables.https://censusindia.gov.in/census.website/data/census-tablesDate: 2011Date accessed: August 29, 2023Google Scholar, 6Ministry of Health and Family WelfareGovernment of IndiaInternational Institute for Population SciencesNational Family Health Survey (NFHS-4) 2015–16.https://rchiips.org/nfhs/nfhs-4Reports/India.pdfDate: 2017Date accessed: August 29, 2023Google Scholar Furthermore, experiencing IPV, particularly psychological abuse and coercive control,7Kalokhe AS Stephenson R Kelley ME et al.The development and validation of the Indian family violence and control scale.PLoS One. 2016; 11e0148120Crossref Scopus (23) Google Scholar is probably underestimated or not estimated by the NFHS, as suggested by our previous work with IPV conceptualisation and scale development in India.8Kalokhe AS Potdar RR Stephenson R et al.How well does the World Health Organization definition of domestic violence work for India?.PLoS One. 2015; 10e0120909Crossref Scopus (28) Google Scholar Second, the sampling bias should be noted. The NFHS only collects IPV data for women aged 15–49 years who have ever been married and in whom IPV data could be collected with an assurance of privacy. Thus, IPV data for women aged 50 years or older were not obtained, 3007 women were excluded due to privacy limitations, and 14 377 women were excluded due to marital status. Women being excluded due to marital status is notable because new relationship dynamics have emerged in India in the past 5 years, especially in metropolitan cities, with increases in dating and non-marital, cohabiting relationships.9Mertia N Emergence of live-in relationship in nexus family laws in Indian context.https://www.khuranaandkhurana.com/2023/04/29/emergence-of-live-in-relationship-in-nexus-family-laws-in-indian-context/Date: 2023Date accessed: August 22, 2023Google Scholar, 10Bhandari P Pre-marital relationships and the family in modern India.https://journals.openedition.org/samaj/4379Date: 2017Date accessed: August 22, 2023Google Scholar In addition, women who were excluded due to privacy limitations might have been more likely to be under the control of their partner. Finally, in addition to dataset limitations, the dissemination of district-level data has the potential to inadvertently stigmatise specific local communities and cause more harm than good if the data are not handled sensitively. There are many future directions for the work from Srivastava and colleagues. First, as well as the dissemination of findings, efforts should be made to sensitise communities and other important stakeholders to the intents of the analysis (eg, informing resource prioritisation in IPV hotspots, locally relevant intervention development, and sharing of effective methods and practices across districts). Second, district-level IPV-estimation efforts should be sustained longitudinally to evaluate the effectiveness of local IPV prevention and other empowerment programmes and policies to subsequently identify districts that should be prioritised. Third, cross-district comparisons should identify additional IPV determinants as targets for future IPV prevention. Finally, the methods of data capture of the NFHS and 2011 Indian Census (eg, IPV measurement or audio-computer assisted self-interview to promote privacy) should be modified to address the limitations mentioned previously. We declare no competing interests. Spatial heterogeneity in intimate partner violence across the 640 districts of India: a secondary analysis of a cross-sectional, population-based survey by use of model-based small-area estimationThis reliable district-level estimation of IPV prevalence in the 640 districts of India has important policy implications. The ability to track substate levels of IPV over time enables the identification of progress in reducing IPV; recognises the heterogeneity of culture and context in India; and informs the targeting of resources, interventions, and prevention programmes to districts with the greatest need. Full-Text PDF Open Access